Wissenschaftliches Seminar
Termin / Date | Name | Thema / Topic | Organization / Organisation | Anmerkung / Remark |
---|---|---|---|---|
08.10.20 - 14:30 Uhr | - | GPT Improving Language Understanding by Generative Pre-Training | Journal-Club / Book Club | Zur Vorbereitung muss folgendes Paper durchgearbeitet werden: https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf |
15.10.20 - 14:30 Uhr | - | Chapter 5 Bayesian Statistics - K. Murphy Machine Learning | Journal-Club / Book Club | bis einschließlich Unter-Kapitel 5.4 |
22.10.20 - 14:45 Uhr | - | BERT - Pre-training of Deep Bidirectional Transformers for Language Understanding | Journal-Club / Book Club | https://arxiv.org/abs/1810.04805 |
29.10.20 - 14:45 Uhr | - | Bayesian modeling and inference via probabilistic programming with pyro | Journal-Club / Book Club | https://pyro.ai/examples/, https://towardsdatascience.com/probabilistic-programming-with-pyro-and-kitchen-scale-f8d6a5d9ae0f, https://gitlab.com/deep.TEACHING/educational-materials/-/blob/master/notebooks/probabilistic-programming/pyro/exercise-pyro-simple-gaussian.ipynb |
05.11.20 - 14:45 Uhr | Rasmus Kiehl, Sebastian Lohmann, Tom Bisson | Daten MAI-Projekt | wissenschaftliches Seminar | |
12.11.20 - 14:45 Uhr | - | Bayesian Methods for Machine Learning | Journal Club / Book Club | Week 1 of https://www.coursera.org/learn/bayesian-methods-in-machine-learning |
19.11.20 - 14:45 Uhr | - | Deep neural network models for computational histopathology: A survey | Journal Club / Book Club | Besprechung des Paper https://www.sciencedirect.com/science/article/pii/S1361841520301778 |
26.11.20 - 14:45 Uhr | - | Bayesian Methods for Machine Learning | Journal Club / Book Club | Week 2 of https://www.coursera.org/learn/bayesian-methods-in-machine-learning, https://gitlab.com/deep.TEACHING/educational-materials/-/blob/master/notebooks/graphical-models/directed/exercise-EM-simple-example.ipynb , https://gitlab.com/deep.TEACHING/educational-materials/-/blob/master/notebooks/graphical-models/directed/exercise-1d-gmm-em.ipynb |
03.12.20 - 14:45 Uhr | - | Image GPT https://openai.com/blog/image-gpt/ | Journal Club / Book Club | Besprechung des Paper https://cdn.openai.com/papers/Generative_Pretraining_from_Pixels_V2.pdf |
10.12.20 - 14:45 Uhr | - | Bayesian Methods for Machine Learning | Journal Club / Book Club | Week 3 of https://www.coursera.org/learn/bayesian-methods-in-machine-learning only part "Variational Inference" and not LDA |
17.12.20 - 14:45 Uhr | - | SimCLR (A Simple Framework for Contrastive Learning of Visual Representations) | Journal Club / Book Club | https://arxiv.org/pdf/2002.05709.pdf , https://amitness.com/2020/03/illustrated-simclr/ |
07.01.21 - 14:45 Uhr | - | SVI with pyro and example Bayesian Regression with Pyro | Journal Club / Book Club | http://pyro.ai/examples/svi_part_i.html http://pyro.ai/examples/svi_part_ii.html http://pyro.ai/examples/svi_part_iii.html http://pyro.ai/examples/bayesian_regression.html http://pyro.ai/examples/bayesian_regression_ii.html |
14.01.21 - 14:45 Uhr | - | Hyperparameter tuning for deep learning / Part I | Journal Club / Book Club | https://arxiv.org/pdf/1810.05934.pdf |
21.01.21 - 14:45 Uhr | - | Monte Carlo Methods / MCMC | Journal Club / Book Club | https://www.coursera.org/learn/bayesian-methods-in-machine-learning/home/week/4 http://www.inference.org.uk/mackay/erice.pdf |
28.01.21 - 14:45 Uhr | - | Hyperparameter tuning for deep learning / Part II | Journal Club / Book Club | Jamieson, K. and Talwalkar, A. Non-stochastic best arm identification and hyperparameter optimization. In AISTATS, 2015: https://arxiv.org/abs/1502.07943 |
04.02.21 - 14:45 Uhr | - | Bayesian Neural Networks: Bayes by Backprop | Journal Club / Book Club | Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, Daan Wierstra: Weight Uncertainty in Neural Networks https://arxiv.org/abs/1505.05424 https://gitlab.com/deep.TEACHING/educational-materials/-/blob/master/notebooks/variational/exercise-bayesian-by-backprop.ipynb |